Human-body communication is a technique for transmitting signals between apparatus connected to a human body by using the human body having conductivity as a communication channel. In the human-body communication technique, a communication network to various portable apparatuses such as personal digital assistants (PDAs), portable personal computers, digital cameras, MP3 players, and mobile phones or a communication network to fixed-type apparatuses such as printers, TVs, and entrance systems can be implemented by a user simply contacting the apparatuses.
An existing human-body communication methods, there have been proposed a method using a limited passband, a method using scrambling with user's unique ID, a method of using channel coding, a method using interleaving, a method using spreading, and the like.
In the existing human-body communication method, a passband having a central frequency fc which is used for most communication systems needs to be used in order to use the limited frequency band. Therefore, a digital-to-analog converter, an analog-to-digital converter, a central frequency converter, and the like needs to be provided to analog transmission and reception stages. Accordingly, the existing human-body communication methods have a problem in terms of low power consumption.
In addition, recently, a human-body communication method using a time-domain/frequency-domain spreading scheme for increasing a processing gain has been proposed. However, due to a limited frequency band, the human-body communication method has a problem in terms of increase in transmission data rate and efficiency of stable data communication.
On the other hand, in case of transmitting or receiving data, error detection is performed so as to check a data-transmission success ratio. In this case, parity bits are used for the error detection and correction.
In current digital communication, various linear block codes for the error correction have been researched.
In general, in the linear block codes including a Hamming code, (n−k) parity bits are added to k information bits, so that the linear block codes constitute a code word having a total of n bits. Encoding of the linear block codes can be simply implemented by calculation of a (k×n)-dimensional generating matrix. In addition, in decoding of the linear block codes, (1×(n−k))-dimensional syndrome bits are calculated by using a ((n−k)×n)-dimensional parity check matrix and a receiving signal, error pattern bits are generated from the syndrome bits, and an XOR operation is performed on the error pattern bits and the receiving signal so as to correct the error included in the receiving signal.
As an example of the linear block codes, in case of setting the number of parity bits to 4, (15, 11) Hamming code is available. In this case, the 4 parity bits are added to 11 information bits, so that a total of 15 bits are transmitted, and 1-bit error correction can be performed. In addition, in case of setting the number of parity bits to 3 (reduced parity bits), (12, 8) reduced Hamming code is available. In this case, 4 parity bits are added to 8 information bits, so that a total of 12 bits are transmitted, and 1-bit error correction can also be performed.